Carbohydrates and Related Biomarkers

This study is designed to investigate associations of low- and high-glycemic load diets with biomarkers of hyperglycemia, hyperinsulinemia and inflammation, potential biomarkers for cancer risk.

Sex

All

Minimum age

18 Years

Maximum age

45 Years

Inclusion Criteria:

1. Healthy males and female subjects
2. Between the ages of 18 to 45
3. BMI between 18.5 kg/m2 to 24. 9 kg/m2 (normal weight) and between 28.0 kg/m2 to 39.9 kg/m2 (overweight)
4. Willingness to refrain from alcohol during the study
5. Able to come to the FHCRC in Seattle every weekday night for dinner

Exclusion Criteria:

1. Younger than 18 years of age or older than 45 years of age.
2. Do not fit into one of the study weight groups (normal weight and overweight): BMI \< 18.5 kg/m2 or \> 40.0 kg/m2, and between 25.0 kg/m2and 27.9 kg/m2
3. Have diseases that are treated by diet and/or medications including but not limited to diabetes, kidney disease, heart disease
4. Taking prescription medications every day (this includes women taking birth-control pills, shots, patch or IUD with hormones)
5. Diagnosed with or treated for cancer within the previous five years (except those with a diagnosis and/or treatment of non-melanomatous skin cancer are eligible)
6. Currently pregnant or breastfeeding or planning a pregnancy in the next 3 months.
7. Using any tobacco products on a daily basis (cigarettes, pipes, cigars, chewing tobacco).
8. Using recreational drugs
9. Drinking the following amount of alcohol almost every day: 2 or more cans/bottles of beer OR 2 or more glasses of wine OR 3 or more ounces of hard liquor.
10. Inability (e.g., food allergy or intolerances) or unwillingness to consume the foods that are part of the feeding study diet.

• DERIVEDHullar MA, Kahsai O, Curtis KR, Navarro SL, Zhang Y, Randolph TW, Levy L, Shojaie A, Kratz M, Neuhouser ML, Lampe PD, Raftery D, Lampe JW. Metabolic plasticity of the gut microbiome in response to diets differing in glycemic load in a randomized, crossover, controlled feeding study. Am J Clin Nutr. 2025 Sep;122(3):780-792. doi: 10.1016/j.ajcnut.2025.06.026. Epub 2025 Jul 5. PMID 40619005
• DERIVEDDibay Moghadam S, Navarro SL, Shojaie A, Randolph TW, Bettcher LF, Le CB, Hullar MA, Kratz M, Neuhouser ML, Lampe PD, Raftery D, Lampe JW. Plasma lipidomic profiles after a low and high glycemic load dietary pattern in a randomized controlled crossover feeding study. Metabolomics. 2020 Nov 20;16(12):121. doi: 10.1007/s11306-020-01746-3. PMID 33219392
• DERIVEDNavarro SL, Tarkhan A, Shojaie A, Randolph TW, Gu H, Djukovic D, Osterbauer KJ, Hullar MA, Kratz M, Neuhouser ML, Lampe PD, Raftery D, Lampe JW. Plasma metabolomics profiles suggest beneficial effects of a low-glycemic load dietary pattern on inflammation and energy metabolism. Am J Clin Nutr. 2019 Oct 1;110(4):984-992. doi: 10.1093/ajcn/nqz169. PMID 31432072
• DERIVEDGinos BNR, Navarro SL, Schwarz Y, Gu H, Wang D, Randolph TW, Shojaie A, Hullar MAJ, Lampe PD, Kratz M, Neuhouser ML, Raftery D, Lampe JW. Circulating bile acids in healthy adults respond differently to a dietary pattern characterized by whole grains, legumes and fruits and vegetables compared to a diet high in refined grains and added sugars: A randomized, controlled, crossover feeding study. Metabolism. 2018 Jun;83:197-204. doi: 10.1016/j.metabol.2018.02.006. Epub 2018 Feb 17. PMID 29458053
• DERIVEDBreymeyer KL, Lampe JW, McGregor BA, Neuhouser ML. Subjective mood and energy levels of healthy weight and overweight/obese healthy adults on high-and low-glycemic load experimental diets. Appetite. 2016 Dec 1;107:253-259. doi: 10.1016/j.appet.2016.08.008. Epub 2016 Aug 6. PMID 27507131
• DERIVEDBarton S, Navarro SL, Buas MF, Schwarz Y, Gu H, Djukovic D, Raftery D, Kratz M, Neuhouser ML, Lampe JW. Targeted plasma metabolome response to variations in dietary glycemic load in a randomized, controlled, crossover feeding trial in healthy adults. Food Funct. 2015 Sep;6(9):2949-56. doi: 10.1039/c5fo00287g.